Corporate Trade War Uncertainty and Patent Bubble

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Abstract

This paper draws upon resource dependence theory and investigates how trade policy uncertainty affects firm strategic innovation management in China. Adopting a machine learning approach called Word2Vec from computational linguistics, we construct and validate a measure of firm-level managers’ perceived trade war uncertainty (TWU). We find that TWU has a positive effect on the number of total patent applications, but this positive effect is totally driven by low-quality patents instead of high-quality patents. Moreover, we document that firms have stronger incentives for such strategic innovation behavior when the underlying firms are more financially constrained, and/or when the management is more myopic. In addition, we open the behavioral black box of firms’ strategic innovation and demonstrate that patents can be employed opportunistically to meet government policies to further attract more government subsidies.

Original languageEnglish
Title of host publication29th Annual Americas Conference on Information Systems, AMCIS 2023
PublisherAssociation for Information Systems
ISBN (Electronic)9781713893592
StatePublished - 2023
Event29th Annual Americas Conference on Information Systems: Diving into Uncharted Waters, AMCIS 2023 - Panama City, Panama
Duration: 10 Aug 202312 Aug 2023

Publication series

Name29th Annual Americas Conference on Information Systems, AMCIS 2023

Conference

Conference29th Annual Americas Conference on Information Systems: Diving into Uncharted Waters, AMCIS 2023
Country/TerritoryPanama
CityPanama City
Period10/08/2312/08/23

Keywords

  • Machine Learning
  • Patent Bubble
  • Strategic Innovation Management
  • Trade War Uncertainty

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